Llama-3-8b-sft-mixture
| Property | Value |
|---|---|
| Base Model | Meta-Llama-3-8B |
| Training Type | Supervised Fine-Tuning (SFT) |
| Model Size | 8 Billion Parameters |
| Repository | HuggingFace |
What is Llama-3-8b-sft-mixture?
Llama-3-8b-sft-mixture is a specialized version of Meta's LLaMA-3 language model that has undergone supervised fine-tuning on a diverse collection of high-quality datasets. Developed by OpenRLHF, this model serves as an essential starting point for researchers working on Reinforcement Learning from Human Feedback (RLHF) projects.
Implementation Details
The model was trained for one epoch on the base Meta-Llama-3-8B architecture using a carefully curated mixture of datasets. The training process focused on maintaining the model's general capabilities while optimizing it for specific use cases through supervised fine-tuning.
- Based on Meta's LLaMA-3 8B parameter model
- Trained on multiple high-quality datasets including ShareGPT, Evol-Instruct, and SlimOrca
- Optimized for research applications in RLHF
- Single epoch training with detailed parameters available in technical report
Core Capabilities
- Enhanced instruction following abilities through diverse training data
- Mathematical reasoning capabilities from OrcaMath and MathInstruct datasets
- Programming expertise derived from Magicoder-Evol-Instruct
- Interactive conversational abilities from UltraInteract and ShareGPT
- Teaching and explanation capabilities from GPTeacher
Frequently Asked Questions
Q: What makes this model unique?
This model stands out due to its specialized training on a diverse mixture of high-quality datasets without RLHF, making it an ideal starting point for RLHF research. Its training combines multiple domains including mathematics, programming, and conversational AI.
Q: What are the recommended use cases?
The model is primarily designed for researchers working on RLHF projects. It can be used as a foundation model for further fine-tuning, experimentation with RLHF techniques, and development of specialized AI applications in areas like mathematics, programming, and conversational AI.
